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Layoffs at Watson Health Reveal IBM's Problem with AI (ieee.org)
Last month IBM, which has staked much of its future on its flagship AI Watson, announced a major round of layoffs in the division. Now the engineers who had been let go allege that the move shows that difficulties IBM is facing in turning its AI into a profitable business. A report on IEEE Spectrum says: "IBM Watson has great AI," one engineer said, who asked to remain anonymous so he wouldn't lose his severance package. "It's like having great shoes, but not knowing how to walk -- they have to figure out how to use it." The layoffs at the end of May cut a swath through the Watson Health division. According to anonymous accounts submitted to the site Watching IBM, the cuts primarily affecting workers from three acquired companies: Phytel, Explorys, and Truven. These companies, acquired between 2015 and 2016, brought with them hefty troves of healthcare data, proprietary analytics systems to mine the data for insights, as well as their customers. The report adds: Two laid-off engineers from Phytel spoke to IEEE Spectrum in depth. They allege that IBM's leadership mismanaged their company since its acquisition, and say the problems at Phytel are emblematic of IBM's struggles to make Watson profitable. Several other Phytel employees corroborated the basic facts of their accounts. Both engineers worked for Phytel since before its 2015 acquisition, and say they were excited to become part of Big Blue. "Everyone expected that we would join IBM and be propelled by their support, that it would be the beginning of great things," says the first engineer.
>> (company) acquires companies, fires acquired employees
This is news because? This is how the world works.
My irony alarms are going off ... layoffs at the AI division!
IBM acquired 3 companies, and with those acquisitions they got "hefty troves of healthcare data, proprietary analytics systems to mine the data" and the customers of the 3 companies they acquired. All those employees are not needed, so they got rid of them.
This is just business as usual.
All the marketing hype about "AI" didn't translate into sales. Here is how to tell a technology doesn't work: Someone comes out with a technology that does X (like plays Chess) and says yeah, but it could be applied to do useful things Y and Z. The question needs to be asked: then why not demonstrate it doing useful things Y and Z? The reason is because it doesn't work. It is really good at X, but they don't know exactly how it can do Y and Z. Meanwhile, billions have been spent on marketing campaigns. Typically taxpayer money is thrown in to support the farce.
and always the monkeys wave arms upon theirs. ginny needs new shoes!
who asked to remain anonymous so he wouldn't lose his severance package
What is the motivation to take this risk? it isn't like the engineer gains anything tangible. IEEE.org gets a few dollars of ad revenue maybe but the engineer gets nothing.
Because in this case, IBM strategy was buying competency in a market they had no footprint in. Not buying a competitor to shutter (which is bad enough).
They proceeded to slap the Watson brand on it, despite no relationship whatsoever to the technology or the people carrying the Watson brand.
This is another chapter in IBM floundering about with the Watson brand, unable to make it profitable after the publicity stunt of the Jeopardy game back in 2011. They've done everything from touting it's ability to generate recipes to medical diagnosis (several times on the medical front, with unrelated technologies at different points in time).
It's indicative of IBM's general annoying tendency to promise that initiative 'X' is going to really turn things around, and then when 'X' is clearly failing to do so, then they rename something completely different 'X' and try again, and rinse and repeat until they (hopefully) can declare 'see, "X" did turn things around!"
XML is like violence. If it doesn't solve the problem, use more.
IBM has a far better record of destroying anything it partners with or acquires.
For the old timers think of Timeplex, Taligent, Pink, OS/2.
About the only things they seem to have going these days are large consulting contracts that are acquired through political connections not technical merit, and legacy Z system support which is still to expensive to migrate.
1- Ask Watson how to make profits
2- ???
3- Profits!
Both engineers worked for Phytel since before its 2015 acquisition, and say they were excited to become part of Big Blue. "Everyone expected that we would join IBM and be propelled by their support, that it would be the beginning of great things," says the first engineer.
Poor deluded former employees. Very few in a merger go on to great things.
But the real thing not so much. This has been true since the 1970's. That does not mean the science hasn't improved a lot.
Sell what the customer wants, deliver what you have only works for awhile.
one engineer said, who asked to remain anonymous so he wouldn't lose his severance package...
In return for a severance package, he agreed not to talk publicly about problems in the company, so... WTF?
That particular employee is not trustworthy. If for some reason his identity gets out he'll be unemployable.
What possible benefit could there be to talk to the media about this? Does the MSM pay for interviews?
I'm baffled by this behaviour.
>> IBM strategy was buying competency in a market they had no footprint in...proceeded to slap (IBM) brand on it
Again, IBM SOP. If IBM (or CA or any other low-contribution, high-licensing-fee behemoth) buys your company, it's usually best to just find a new company and wait for the buyout package.
The problem IBM has with Watson is that nobody knows how it works or what logic pathways lie behind it. Normally a company like Microsoft or IBM would have hordes of developers who work for companies, and somehow they find their niche in that equation while the developers figure out end uses. IBM, though it's supported Linux and open source for years, has a major difficulty with documentation for end users (to put it quite mildly) and has decided to keep the logic for Watson proprietary. Good luck with that.
I've worked with a number of companies acquired by IBM, and what you say is mostly true. This time was unusual as they *really* did seem to try to use that team for a few years before ultimately giving up. They seemed to genuinely think they were unable to win without those people, then the sentiment seemed to become they can't win even with those people, not that they were winning and could cut the team as a result.
XML is like violence. If it doesn't solve the problem, use more.
profitable business? put in some game shows it can win a lot of them
I'm surprised IBM hasn't gone into security and SDN world with the Watson yet, or have they? They are publicly playing games with an area that is currently more suitable for other technologies in terms of low hanging fruits, or difficult and expensive to make products in. No wonder the layoffs for this particular Watson division.
I have worked for several companies that were acquired by IBM. Wholesale layoffs are not surprising, similar to them wanting to convert people to contractors in order for them to keep their positions. In any case, when IBM buys your company, start polishing up the ol' brag sheet because they will be coming to "separate" you soon after that, and be ready to take the severance package.
Just be glad you are an IBM-er. From what I've encountered, contractors don't even get fired face to face. They get their badge disabled, and told to leave the premises or face arrest for trespass. I personally would avoid IBM at all counts because of how shabbily they treat their staff, unless you get a management job. IBM managers are pretty much there for life, as good as it gets outside a GS position.
the cuts primarily affecting workers from three acquired companies: Phytel, Explorys, and Truven. These companies ... brought with them hefty troves of healthcare data, proprietary analytics systems to mine the data for insights, as well as their customers.
Notice that IBM didn't layoff the data, proprietary analytics systems or customers.
It must have been something you assimilated. . . .
Back in the old days, the saying used to be "you'll never get fired for buying IBM".
Today? If I was a manager and someone uttered as many as 2 of the 3 letters...I'd can that fscker right on the spot.
Light travels faster than sound. This is why some people appear bright until you hear them speak.........
IBM does have a great piece of technology that could streamline a very complicated and expensive part of health care. Unfortunately health care has a huge amount of regulation that I suspect is in many places self contradicting. Watson should be profitable and at the same time it should also bring down my healthcare costs. Unfortunately Watson will require a large company with deep pockets to handle all the regulations and also a company competent at handling complex computer systems. IBM can't do large complex systems and hasn't been able to for 30 years. They don't have the organizational physiology and if even if that changed they don't attracted the types of employees who have that skill set. Amazon could probably do it, maybe Walmart (Walmart an incredible logistics company that happens to have retail stores) but after that I can't think of anyone else (kaiser permanente or one of their competent competitors???)
IBM Watson simply doesn't work. It's too generic and businesses try to use it to fulfill niche business needs and it's doesn't work as advertised.
That all happened after Gerstner - an ex-McKinsey "management consultant" - took over. That mentality of "maximizing shareholder value" (i.e. keep the stock price going up by all means) is what turned a company into what it is today.
The old blue chip companies are turning or have turned into shit: Kodak, GE, IBM, DEC, .... Because of the "maximize shareholder value" mentality. Kodak could have kept up with changing markets but doing so would've hurt the bottom line in the short term.
And along with them went the days of working at a company for your life and retiring with a nice pension. Treating workers like that "hurts" shareholder returns - in other words, the shareholders don't make as much money as fast.
Just another way the worker is being shafted for the 1%.
never mismanaged??????
Ok
The problem is that they focused on the wrong industry. Healthcare in America is bloated and inefficient at 18% of the economy, double any other country. But, while many other industries are "bottom heavy" with plenty of powerless assembly line workers or clerks whose jobs can be automated away or shipped overseas, healthcare is "top heavy" with a vast number of professionals represented by powerful organizations.
Decades ago it was obvious that many doctors could be replaced, since a nurse using a paper checklist could diagnose with the same accuracy. This is exactly what was done in many countries, with nurses or PAs handling the routine cases, while referring the difficult cases to MDs. But in America, we instead got an institutional resistance to any reform that could reduce profits. There are no incentives for doctors, or patients, or insurance companies to control costs. It is no surprise that IBM was not able to change this. What is surprising is that they thought they could.
Sounds like Watson is perfect for automating the White House.
-6 Too Political
Table-ized A.I.
>> many doctors could be replaced, since a nurse using a paper checklist could diagnose with the same accuracy. This is exactly what was done in many countries, with nurses or PAs handling the routine cases, while referring the difficult cases to MDs. But in America, we instead got an institutional resistance to any reform that could reduce profits
Don't know if I agree. Within the past ten years (and corresponding to a massive increase in cost of care) I've seen a lot of "Nurse Practitioners" step in where I used to see doctors with the kids when they were younger.
>> There are no incentives for doctors, or patients, or insurance companies to control costs
Maybe not doctors, but there are now tremendous incentives for companies and employees to control costs. So, we use the $XX company nurse/doctor instead of the $XXX option available under our health care plan. And we try to stay as far away as possible from any Urgent Care or ER services.
What seems to be driving the massive cost increase is that free care is increasing, government payments are capped, and the surviving health care providers are squeezing the last handful of us who can still pay the bills. Meanwhile, no hospital system wants to stop building hotel-quality hospitals with huge atriums ("atrium...get it?") and chasing plastic surgery patients (which requires keeping up appearances), so they keep spending like coke addicts. All we're asking for out here in the middle class is change, which is part of the reason Bernie almost won and then Trump did win. Unfortunately...
"IBM Watson has great AI," one engineer said, who asked to remain anonymous so he wouldn't lose his severance package. "It's like having great shoes, but not knowing how to walk -- they have to figure out how to use it." The layoffs at the end of May cut a swath through the Watson Health division.
The path to money is replacing doctors. Duh. Partner with insurance companies that PAY YOU to make doctor Watson the initial contact for their customers.
You call in, or log in and give it your symptoms, answering it's questions (Maybe sending it photos). It gives you a diagnosis, advice, a prescription, and/or refers you to a specialist or a bloodwork lab.
That means giving Watson the authority of a real doctor, that can actually DO things like diagnos and write prescriptions. And that means making it liable for fucking up. If Watson is good, then that should be viable.
This makes money for Watson and that dev team, they get paid by the insurance companies. This makes money for the insurance companies as the rate for one computer on the Internet is hella cheaper than all those general practioners. This is a general improvement for the customers as their doctor is on tap 24/7 and doesn't have a hideous co-pay.
This screws over doctors who will undoubtedly become neoluddites or further specialize.
This screws over Insurance companies that don't actually want you to make use of them. They make money off of healthy people that carry the policy just out of fear. If you actually USE the insurance, the insurance company loses money. To that extent, health insurance companies anything that makes the health-care system simpiler and easier to use. And thus we see why IBM can't appear to sell Watson.
We need AI for justice to speed up processes, not on health. Thats my big dream.
You obviously have not been to a doctors office. You will almost always see a nurse or PA and not a physician. Been that way for a while now.
Another fact free post from Shanghaied Billy.
"Decades ago it was obvious that many doctors could be replaced, since a nurse using a paper checklist could diagnose with the same accuracy"
I'm not aware of any studies of substance that substantiate such a bold claim. I am aware of some weak studies looking at NPs managing chronic diseases that had already been diagnosed. Perhaps that is what you are referring to?
"This is exactly what was done in many countries, with nurses or PAs handling the routine cases"
Really? Most health care providers in Europe and Australia have never heard of or worked with a PA or NP. Further, I've never heard of their nurses making diagnosis or managing diseases.
I work for an international health care company so I have some idea of the lay of the land here. If you have some sources to back this up, I'm interested. Otherwise, I'm fairly sure this is just BS.
Most employees are Indian!! Go back to India !!!!
... and chasing plastic surgery patients ...
It is ironic that you mention cosmetic medicine as a reason for runaway costs. Actually, the opposite is true. Cosmetic medicine is one area that has NOT seen costs skyrocket, and for many treatments prices have declined. The reason is that cosmetic treatments are generally not covered by insurance so patients are paying out of their own pocket. Prices are listed upfront, and the prices are often openly published in advertisements, something that is not done in almost any other area of medicine. It is one of the few areas of healthcare with a functioning free and competitive market.
Another area that has seen dramatic declines is corrective vision treatments. I paid $3000 for LASIK back in 1999. Today, the same clinic charges $299 per eye. This is another area generally not covered by insurance, and with upfront pricing.
What possible benefit could there be to posting on Slashdot? Yet you are doing it.
You can't come up with a reason for posting - so there's none?
I post on Slashdot specifically to practice writing and debating skills. It gives immediate feedback, so meshes well with Gladwell's "20,000 hours of practice" theory.
I also post to help innoculate myself against insults and reduce my dependence on "what other people think", a character flaw of mine that many people have. (Note: I don't consider your response matching one of those.)
I can understand the need to talk, and for social empathy and all that.
It's just that to make a promise and enter into a binding agreement (for money) and then *break* that promise...
Is the need for social empathy so great that people will take a chance on ruining their lives for it?
It doesn't *seem* like a good trade-off, but then I'm less on the emotional side of things than most people.
Nurse practitioners are now in place in British Columbia, Canada. It is questionable whether there are cost savings.
...is that we expect these machines to teach themselves, i.e. make meaning out of what they experience (data that is input). There's only so much you can achieve through poor investigative practices like p-hacking. Yes, AI can find lots of interesting patterns and regularities in data but which ones are meaningful/useful? It's better to start with questions and go from there; specify what data is relevant/salient, where it is, how to get it, how to model and interpret it, how to control for variables, etc.. We've had a pretty good investigative toolbox since Karl Popper came up with the modern scientific method. Why don't we try to get technology to use it?
Debate is a form of harassment. Do not question my truth.
Seems like the first task for any AI team...if you can't solve that problem, then maybe the dog food isn't as good as they say...
True, Canada does have NPs. I am aware of that - it was a oversight on my part because a lot of the work I do considers Canada domestic, even though they really aren't.
Anyway, most countries do no use NPs or PAs. As you said, there is no evidence they save money.
In the US, about 10% of all expenditures go to physician fees so even if they did save money, its not the kind of money they will be a big difference maker.
Hard to make it profitable = We cant come up with a good lie that will convince anyone firing humans and replacing them with AI is good for anyone other then corporate profits/stockholder/business owners.
Jack of all trades,master of none
Read and understand the tax code.
Then do a better job on taxes than TT
So why didn't IBM apply Watson to fields of science like Mathematics or Physics. Most of the discoveries that get announced are due to someone realizing that two apparently unrelated fields are actually related after all, and creating a shortcut in writing proofs.
Vintage computer adverts: http://www.vintageadbrowser.com/computers-and-software-ads
You clearly do not work in Mathematics or Physics. Go ahead and let AI "learn" from the Mathematicians and Physicists, it will produce nothing of value. AI doesn't create anything new, it merely optimizes what's already known.
I grew up when IBM was the most amazing company in computing. They did big and small and you could walk into a store and buy a computer with the name IBM on it. When the PS/2 came out, I spent years drooling and wishing I could get one of those. I'm sure a PS/2 Model 50 with a 286 would have made my life worth living.
... I wish everyone involved luck.
Then IBM progressively decided that they wanted to blacklist all the people like me. I have absolutely no idea where to start if I wanted to start doing anything with IBM today. I've honestly tried too. I have been trying to get myself a CICS environment to develop software for as I'm building a system which could benefit from it. The problem is, I don't want to be stuck in a room with sales people. I just want to download an image and try it out. I want an environment which can run on my laptop which I can develop on over the summer while on a train ride across Europe. I've been told I can use Hercules, but I can't figure out where to start. The entire IBM community is completely closed off and people act so superior as though "You could do this, but it's too hard for you".
So, instead I'm building my own OLTP system based on Couchbase instead of DB2 and using OpenFaas (and extending the hell out of it) instead of CICS.
I made this little rant to explain why I've never considered using Watson.
If I'm going to develop a system on an AI technology, even if it's inferior and years behind, I'll use Microsoft, Google or Amazon's solutions. The reason is that all 3 of them are approachable. It's possible for me with a free account as a developer to do what I need to do and then check the code into our corporate codebase and send the business people in rooms together and sign contracts. I don't need to sign my life away only to feel locked into a technology which may or may not be able to do what I need. I can actually make hobby projects and experiment with the technologies outside the IBM world, learn them and then use them.
I honestly always thought Watson was cool and I've had uses for the technology I'm sure. I also have 7 digit budgets to spend on technologies I need. But I doubt the money will ever get to IBM because I'm pretty scared of them. What's worse is that I'm scared that if I let them in the door, they won't be happy with the money I'm offering, but instead will bully me and my bosses into signing contracts that are 10 times bigger because they're goal is to milk us for everything. I've always heard that everyone who ever used IBM was really happy until they realized they were paying $5 million for a web site.
Well... I'm off to write my OLTP
would making WATSON an open source product be useful for various medical therapies?
it is well documented that IBM would take steps to have a person black listed if they worked with IBM stuff and preferred not to.
I'm genuinely curious - what are the top three expenditure categories in the USA, and their percentages?
Current (unwilling) IBM customer here. You're right - run like hell away from them. Treat them the same way any sane person does when offered Oracle software: "No fuckin' way".
They're happy to take my money. Getting support from them is a joke and the prices just keep going up for less and less. When they ask why I don't buy product X or solution Y I consistently tell them how much I hate system Z that I'm stuck with and how many times they've dropped the ball with it. Then they change our reps and we do the same dance again in 4 months.
The only connection between Watson Health and Watson AI is the name. Watson Health is all about patient management software, with no trace of AI at all.
Drugs
In the US, about 10% of all expenditures go to physician fees
Do you have a citation for this factoid? It seems wildly implausible.
How good is at at using apostrophes? Or rather, *not* using them?
What seems to be driving the massive cost increase is that free care is increasing, government payments are capped, and the surviving health care providers are squeezing the last handful of us who can still pay the bills.
Nope, it's because of the insane profits. Your healthcare is expensive because you have the worst possible system.
This is not even controversial, you pay more and receive less than other western countries because so much of what you pay goes to make the healthcare companies lots and lots of money.
Companies that start with an innovative founder who had a great idea, then become gigantic and publicly-traded, then move from a retired/dead founder to a hired-gun CEO, a raft of middle-management MBAs and a board tend to become inertia-driven, inflexible, and incapable of altering course even with disaster looming.... they become like large jets on autopilot aimed at a mountain. The executives are all asleep (everything's great and always has been after all...) in the cockpit and the corporation is on "altitude hold". If the execs were awake, they'd see the mountain ahead in the window and if they actually knew how to fly they could avoid the mountain, but they're on a plane that has always been flying well and they have generic business/management degrees that never taught them how to actually bank and climb or dive...they certainly never learned how to take off or land or navigate.
IBM is likely to go the way of Sears and Motorola and any number of other such famous market-dominating brands. Its executives all have golden parachutes and expect to do no real work and take no real risks; they landed spots at these corporate giants as a cushy way to make even more money before retiring. Unlike the people who created and grew these businesses in the first place, these hired guns have no personal investment in the long-term success of the businesses they run, since they're only in it for a few years late in a career and are not themselves "hungry".
IBM dominated computing. There's simply no excuse for management there who had access to an enormous mountain of IP, cash, brand reputation, and talent, and infrastructure failing to stay #1. Anybody in management at IBM in the past 20 years should be blacklisted as insanely incompetent and not to be allowed near the offices of another business.
Sears (another similar example) dominated mail-order retail - they were "the original Amazon.com". There was a time when anybody anywhere in America could order and have delivered aanything they needed by contacting Sears. There's simply no excuse for management there who had access to an enormous mountain of cash, brand reputation, experience, and infrastructure failing to stay #1. Anybody in management at Sears in the past 30 years should be blacklisted as insanely incompetent and not to be allowed near the offices of another business.
There are many more examples like this; it seems that we need a new "law" (in the sense of Murphy and Godwin) about companies that go big and market-dominating, then transition to generic CEOs and managers who are all hired guns with no tie to what made the company great in the first place and thus no idea of how to make it greater or even keep it great.
I think more the question is do people trust machines and technology to replace humans who are obviously fallibable but people still seem to trust people more. It’s sort of like VR and AR they have some really neat demos but how to realistically apply it to real world solutions is another thing.
'Layoffs at Watson Health Reveal Problem with AIin General'. FIFY There is no 'AI', and expecting software to magically do things software cannot do should probably be a definition of insanity, or at the least a gross misunderstanding of what actually constitutes intelligence.
It shows that AI is working !!!
The two care areas you mention, cosmetic surgery and lasik, are both elective. Most patient-customers could choose not to do any such procedures and still live a fine life (though with glasses on, or smaller breasts, or whatever). The rest of medical practice, where if you do nothing you eventually have life-altering problems or die, are the environment where (a) the patient isn't really a customer as much as they are a supplicant, and (b) hiding costs works really well.
Once I show up at an orthopedic surgeon with a broken ankle, the chances that I'll go doctor-shopping are low. If the fees and complication rates were available on the web before I get in the car, it would be a completely different story.
Why is it that neckbeards get so bothered by physicians?
There is the old saying that if you think you know the solution, you do not understand the problem. That seems to apply to a lot of technology acquisition in the health fields.
Here is the problem. In medicine, there are some disorders and diagnoses that are very well understood in terms of physiology and pathogenesis, well characterized as to making a correct diagnosis that correlates with an effective response to prescribed treatment, and easy to teach to young physicians who can in turn provide accurate diagnoses and good care to people with those problems.
However, there are also problems that are oddball or non-obvious diagnoses, problems due to occult or infrequent disorders, problems with atypical symptoms or atypical responses to intervention, or else problems that reflect altered or atypical pathogenesis or else disorders of complexity or dysdynamia in complex multi-control systems in which one person's illness has different signs and symptoms than the next person with the same illness. If compared to algorithmic processes such as computer programming, some of these patients and problems would be seen as illogical, out-of-sequence, or data corrupted, yet a valid diagnosis can be made by someone who understands these deeper levels of seeming illogic. Whether or not contemporary doctors and medical education still rise to the challenge is another issue altogether, but when medicine is done right by smart properly educated physicians, correct diagnoses and treatments can be made for very non-obvious problems. This is because genuine intelligence is better than artificial intelligence at doing these non-obvious complex tasks.
But, you say, therein is the value of AI, indeed the whole premise of AI, that it can perceive patterns and associations in data that even smart people will not necessarily see. That may be true, but AI can be no better than the set of data it is trained on. The article states "these companies . . . brought with them hefty troves of healthcare data, proprietary analytics systems to mine the data for insights". Big databases from corporate healthcare enterprises do indeed have lots of data , but it is not necessarily quality or robust or relevant data. It is the kind of perfunctory or bulk data that is filled out into forms, or is coded in ICD and CPT numbers (industry standard diagnosis and procedure codes). The data is curated or trivialized to what can be entered by overworked professionals in order to generate bills, or else by low level billing and data clerks. It is often data that is not relevant to the technical medical issues, and even when it is, it is not the detailed or nuanced data that allows for the oddball, atypical, and one-off diagnoses.
Suppose there are 7 different disorders that can affect the pinky toe, 3 of which are common and readily recognized by medical students and physician extenders, 2 more of which are recognized by the average properly educated physician, and 2 of which are odd and likely to be recognized only by experienced experts. The difference in diagnosis for these latter two might be because the toe points at an angle five degrees different than normal. If the data keeping records have only 4 approved codes to recognize 7 diagnoses, and if there is no place to record the angle of the toe, then the AI training set will not be able to understand the oddball diagnoses. Note as well that the data entry front ends that are often in modern medical records depend on the easy info. The problem is that the easy diagnoses can already be made by people with a baseline education. The one-off diagnoses depend on levels experience of multi-factorial observation and pattern recognition that real experts have but which the medical record is often scant on.
Technology has become a self-indulgent plaything for companies and venture capitalists. "Let's automate or computerize this or that . . . because we can. Isn't this fun?" If you develop enough infrastructure or visibility or limited success to beguile the next dog up th
âoeYou clearly do not work in Mathematics or Physics. Go ahead and let AI "learn" from the Mathematicians and Physicists, it will produce nothing of value. AI doesn't create anything new, it merely optimizes what's already known.â. I have a book on my shelf titled âoeAutomated Theory Formation in Pure Mathematicsâ. The existence of this book refutes your claim. I would gather that that watson has not been applied to fields such as mathematics and physics because it was designed as a QA system rather than as a system to prove theorems or solve constraint problems.
It really depends on what it is your are trying to assess and who you believe. If we are trying to determine the total amount of the expenses that eventually lands in the doctors actual income, 10% seems to be the most widely accepted number. If you go to the CMS website, in their expenditure reports the category "physician and clinical services" is listed as 20% of their expenditures in a given year. Some people quote this value; however, this percentage includes more than just take home income to the provider - it includes equipment and other overhead expenses, I believe. Thus, some chunk of this will never make it to the physician. (this is a little out of my area of expertise but it is something like this). On the other hand, some sources will claim the actual percentage is as low as 5%. Some groups will use this number but my memory is this is a somewhat disingenuously low percentage because it leaves out some less common methods by which a physician can make money from today's system (such as owning their own surgical center). Most experts believe all things considered the true percentage in the US is about 10%. This is actually lower than many other countries when looked at as a percentage of total expenditures.
I know someone who is an expert on these matters and runs a company geared towards helping insurance companies both save money and improve quality. She often says, "Can you really afford to hire the cheapest doctors?" This is because doctors, NPs and PAs generate a huge number of tests, referrals and such whose costs far exceed what that practitioner makes. On the whole, a high quality physician vs a lower quality one will order fewer tests and make fewer referral by sticking with best practices and will overall save resources.
Insurance companies _absolutely_ want to reduce costs. So do companies who pay premiums. I've been stuck seeing Nurse practitioners for heart palpitations since they started.
That other 9% is profit to insurance companies and big Pharma. IBM tried to muscle in on their territory. That IBM failed is a testament to how much power insurance & pharma wield.
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Try bluemiz
I don't know about AI, but computer programs have proved some theorems.
I've worked with linear algebra and statistics for various projects. I've visited websites like encyclopediaofmath.org and have always wanted to see how all the different topics relate to each other in a graph network visualization format. Then be able to find the shortest path between two topics.
Vintage computer adverts: http://www.vintageadbrowser.com/computers-and-software-ads
Maybe they'd be profitable if they didn't pay them $300-500K. https://www.nytimes.com/2017/1...
Is this opposite day?
Here in the U.S. it is rare that you ever get to see an actual doctor.
We asked IBM for Watson's data analysis capabilities, IBM came back with a POC proposal in the hundreds of thousands of dollars. We went with Google for a fraction of the cost.
Start small and build it up. Google is capitalizing on that concept. IBM is being left behind in this space because they want people to chew more than they can handle.
IBM Watson has great AI. It's like having great shoes, but not knowing how to walk -- they have to figure out how to use it.
This sums up the difference between science and engineering: one asks what if, the other starts with the desired outcome then asks how.
Opensourcing an AI tool does nothing. The value is on its training... not on its code.
You could say Newton didn't make anything new (forget about his lenses for a moment) in his general gravity models.
But wasn't it a big discovery?